Wavenumber-domain (WD) sparsity has recently demonstrated great potential in enhancing channel estimation performance for holographic MIMO (HMIMO) systems. However, existing channel estimation studies exhibit several shortcomings, e.g., large search space and inability to fully exploit block-sparsity. In this paper, we study the sparse WD channel estimation for HMIMO systems under non-line-of-sight (NLoS) environments. Specifically, a two-stage orthogonal matching pursuit (TS-OMP) algorithm is first proposed. It exploits a reduced search space: the first stage applies simultaneous OMP (SOMP) to obtain row and column supports, and the second stage reconstructs the channel within this reduced space via OMP. Furthermore, we exploit the block-sparsity of the WD channel and propose the reduced search space-block sparsity (RSS-BS) algorithm. The RSS-BS algorithm is also a two-stage algorithm and differs from the TS-OMP only in the first stage. Concretely, the row and column supports are acquired by utilizing the channel clustering characteristics in the 2D wavenumber indices at the transceiver, given the initial estimation obtained from the conventional WD-OMP algorithm. Finally, simulation results demonstrate that the proposed algorithms achieve much better estimation performance than the conventional WD-OMP algorithm.

Reconfigurable holographic surfaces (RHSs) can generate the desired directional beam by controlling the radiation amplitude of reference wave, and thus is an effective alternative to conventional analogue beamforming architecture. In this paper, we investigate the RHS-aided downlink multiuser multiple-input-single-output system with one-bit digital-to-analogue converters. Specifically, we aim to minimize the mean-square error by alternately optimizing the one-bit precoding vector and the holographic beamforming matrix. The alternating direction method of multipliers algorithm is employed to optimize the one-bit nonlinear precoding vector, and the projected gradient decent method, the mathematical programming with equilibrium constraints-alternating direction method, and the Riemannian conjugate gradient method are utilized to design the holographic beamforming matrix with continuous amplitude, binary amplitude, and Lorentzian-constrained phase, respectively. Finally, the effectiveness of the proposed method is demonstrated by computer simulations.

Recently, active intelligent reflecting surface (IRS) has attracted much attention because it can solve the double-fading attenuation caused by cascaded channels. In this paper, the one-bit precoding vector at base station and the reflecting matrix at IRS are optimized jointly to minimize the mean squared error in the sub-connected active IRS-aided multiuser multiple-input single-output system. The resulted optimization problem is non-convex, for which an efficient alternating optimization algorithm is proposed. Concretely, the alternating direction method of multipliers, coordinate descent, and accelerate proximal gradient are utilized to optimize the one-bit precoding vector, discrete reflecting phase, and amplification factor, respectively. Finally, computer simulations are given to verify the proposed method in terms of energy efficiency and bit error rate.

In this paper, we study the coexisting scheme including common alarm messages with correlated user activity and standard messages with uncorrelated user activity in the multipleinput multiple-output grant-free non-orthogonal multiple access. Concretely, all the potential users are divided into multiple groups each monitoring an additional alarm event besides the standard message transmission. Active users transmit the superposition of standard messages and alarm messages if the alarm events are triggered and detected, and transmit only standard messages otherwise. Moreover, the alarm message is transmitted by utilizing the principle of index modulation. At the base station, the Turbo approximate message passing algorithm is designed to realize the joint user activity detection, channel estimation, and alarm information decision. Finally, computer simulations are provided to verify the effectiveness of the proposed scheme.

Grant-free non-orthogonal multiple access (GF-NOMA) is considered as an important technology in massive machine-type communications. In this paper, we study the multiuser detection (MUD) of uplink GF-NOMA with temporal-correlated active users. To utilize the temporal correlation in both directions, the bidirectional (BD) side information aided (SIA) compressed sensing (CS) MUD is proposed here for both the cases with known and unknown user sparsity level. Concretely, the bidirectional dynamic CS MUD (BD-DCS-MUD) is first proposed in the case with known user sparsity level. In BD-DCS-MUD, the temporal correlation information between adjacent time slots in both directions is utilized by performing forward DCS-MUD followed by backward DCS-MUD. For the case with unknown user sparsity level, the SIA sliding-window block orthogonal matching pursuit (SIA-SW-BOMP) is proposed. In SIA-SW-BOMP, the backward temporal correlation information is also utilized by SW decoding strategy, besides the forward information utilization through BOMP. Simulation results show that the proposed BD SIA CS MUDs can achieve better performance than their forward counterparts especially for the scenario of large user sparsity level, with some increased complexity.

In this paper, dual-functional radar-communication system which can perform both radar and communication functionalities using the same hardware platform and spectrum resource is studied. Concretely, the mean-squared error between the designed and desired beampatterns is minimized subject to the communication quality-of-service requirements and the constant-modulus constraint. To solve this resulted problem efficiently, the alternating minimization framework is presented. Specifically, in the sub-problem of transmit signal design through symbol-level precoding, the low-complexity linearized alternating direction method of multipliers algorithm is presented. Finally, computer simulations are given to demonstrate the effectiveness of the proposed method.

Recently, the application of intelligent reflecting sur-face in wireless communications has attracted considerable attention. In this paper, the precoding of IRS-aided multiuser multiple-input single-output systems with one-bit digital analog converter at base station and discrete reflecting phase shifter at IRS is studied. The non-linear one-bit precoding and discrete phase are optimized jointly to minimize the mean square error. To solve this optimization, the alternate minimization strategy is employed to optimize precoding vector and discrete phase alternately. Moreover, the optimization for both constant-modulus phase-shift-keying (PSK) and general quadrature amplitude modulation (QAM) are considered. Concretely, the alternating direction method of multipliers algorithm and coordinate descent method (CDM) are utilized to acquire the one-bit precoding vector for PSK and QAM, respectively. In both PSK and QAM, CDM are employed to acquire the discrete phase optimization. Finally, computer simulations are given to demonstrate the effectiveness of proposed method.

In this paper, the uplink sparse code multiple access over universal filtered multicarrier (SCMA-UFMC) in rapidly time varying channels is studied. In SCMA-UFMC, each subband of UFMC is occupied by multiple users through SCMA. It is observed that the inter-band-interference can be neglected and both the inter-carrier interference and inter-user-interference are small from the equivalent frequency-domain (FD) channel of even component of received signal. Based on this observation, message passing algorithm is first employed to perform multiuser detection (MUD) by utilizing only even-component of received signal. Next, to improve the performance, a two-stage detection is further presented, where the unreliable estimates from the first-stage detection using even-component are refined by utilizing additional odd component of received signal. Finally, simulation results are given to demonstrate the performance of the proposed methods.

In this paper, the massive multiple-input multiple-output un-sourced random access (URA) is studied, and an index modulation (IM)-aided transmission scheme is proposed. The proposed URA-IM scheme is built on the conventional URA consisting of common inner compressed sensing (CS) code in all channel blocks and outer tree code across blocks. Different from conventional URA, URA-IM firstly partitions channel blocks of one transmission frame into multiple groups, and then employs the IM principle to activate only part of the channel blocks in each group. By URA-IM, the average number of active CS codewords in each channel block can be decreased, which will improve the performance of inner CS detector. Moreover, a modified tree decoder is proposed to take the IM signal property into account. Computer simulations show that the proposed URA-IM has better performance than conventional URA in terms of permitting shorter block length and servicing more active users in the scenario of 36-bit information transmission per user.

In this paper, the massive multiple-input multiple-output un-sourced random access (URA) with dynamic user activity (DUA) is studied. The transmission frame consists of multiple blocks, and here DUA means that active users are block synchronous other than frame synchronous, i.e., the user activity is dynamic in different blocks of the same frame. To implement the URA with DUA, a multiple-codebook-aided concatenated scheme consisted of outer tree code and inner compressed sensing (CS) code is proposed. Concretely, four CS codebooks with same size are employed in inner CS code design to adapt to five typical transmit patterns in URA with DUA. Moreover, a modified tree decoding is presented to stitch the transmit information sequences of dynamic users. Finally, computer simulations are given to demonstrate the effectiveness of the proposed scheme.

In this paper, a non-coherent transmission scheme in cloud-radio access network (C-RAN) for machine-type communication (MTC) is presented. In the proposed scheme, each user is allocated multiple unique pilot sequences, among which part of pilot sequences is activated and their superposition is transmitted when this user is active. The data information is then conveyed by the indices of active pilot sequences utilizing the index modulation principle. At receiver, non-Bayesian maximum likelihood detection is derived to identify the active user and recover the data information simultaneously. Moreover, the detection for quantized received signal in the case of limited-capacity fronthaul link is also presented. Finally, simulation results are given to demonstrate the performance of the proposed non-coherent transmit scheme.

Massive MIMO un-sourced random access (URA) is a promising massive random access technique for massive machine-type communications. The conventional receiver of uplink URA consists of inner covariance-based multiuser detection (CB-MUD) and outer tree-based decoding, and its performance is highly dependent on the threshold used to determine the activity state of transmit codeword in CB-MUD. In general, this threshold is involved with multiple system parameters, and difficult to optimize. In this paper, an iterative receiver consisting of CB-MUD and outer decoding is proposed. In this iterative receiver, the successive interference cancellation (SIC) strategy is employed, where the covariance information associated with codewords decided in the former iteration is peeled off and the residual covariance is used for CB-MUD in the latter iteration. Noting that the sparsity increases with iterative number, in general, the performance of CB-MUD can be improved which is demonstrated by simulations. On the other hand, multiple iterations can relax the requirement of threshold selection. Concretely, an empirical formula for the threshold setting which decreases with iteration number is presented, and its robustness to system parameters is also verified by simulations.

Universal filtered multicarrier (UFMC) modulation has attracted much attention recently due to its potential advantages over orthogonal frequency division multiplexing. In this paper, the signal detection of UFMC in rapidly time varying channels is stuided. It is first observed that the frequency domain (FD) channel associated with even component of received signal can be well approximated by a band matrix centered along main diagonal and that associated with odd component can be approximated by block-diagonal matrix with some inter-sub-band-interference (IBI) between adjacent blocks. Based on this observation, an initial estimation is first acquired by Viterbi algorithm using the even component. Then, this estimation is refined block-by-block by utilizing the low out-of-band emission using the odd component. Moreover, considering the IBI between adjacent blocks, a sliding-window strategy is introduced to further improve the detection performance. Finally, simulation results are given to demonstrate the effectiveness of the proposed detection.

In this paper, we study the nonlinear one-bit pre-coding in the massive multiple-input multiple-output downlink system. Different from the conventional criterion of minimizing the sum of mean squared error (min-sum MSE) of all users, the criterion of minimizing the maximum MSE (min-max MSE) is considered here which is more suitable for communications in block and slow fading channels. Based on this min-max MSE criterion, two methods are proposed to optimize the precoding vector and precoding factor. In the first semi-definite relaxation (SDR) method, the min-max MSE problem is first formulated as a semi-definite programming problem with non-convex rank-1 constraint, and then SDR is employed to relax this constraint. The output of SDR is further processed by Gaussian randomization procedure, where, for each candidate precoding vector generated according to the output of SDR, the precoding factor is solved by the quadratically-constrained quadratic programming. To reduce the complexity, the second method employing two-stage processing strategy is further proposed. In the two-stage precoding, the initial solution is first acquired by the efficient alternating direction method of multipliers for the min-sum MSE problem, and then refined to achieve better min-max MSE performance by the symbol-flipping (SF). Finally, the proposed methods are demonstrated by computer simulations.

The signal recovery of the uplink grant-free nonorthogonal multiple access system is a challenging problem in random access of massive machine-type communications. In this paper, we propose a low-complexity parallel adaptive subspace pursuit (parallel ASP) algorithm. First, the signal recovery problem is converted into multiple single measurement vector compressive sensing (SMV-CS) problems. Then, the multiple SMV-CS problems are solved by ASP algorithm in parallel. Furthermore, an outer iteration is introduced where the information exchange strategy is designed to leverage the block-wise sparsity. Simulation results show that the proposed algorithm can reduce the computational complexity enormously with only small performance loss compared with conventional block sparsity ASP algorithm.

This paper presents a nonbinary low-density parity-check (LDPC) coded spatial modulation (CSM) for multiple-input multiple-output communication systems, in which the information bits for choosing active transmit antennas and the bits for choosing constellation signals are protected by a nonbinary LDPC code. We apply a many-to-one mapping known as Gallager mapping to signal constellation, resulting in an improved constellation design for the CSM system. Furthermore, we propose a Gallager mapping-based scheme to solve the design problem of the CSM system with arbitrary transmit antennas, in which Gallager mapping is used to map the index information bits to the active antenna, thus an integer-bit transmission can be achieved for any number of transmit antennas. With the use of nonbinary LDPC codes, a non-iterative receiver is able to recover the undistinguished information caused by the many-to-one mapping. Several communication scenarios are studied and simulation results show that the proposed scheme can offer substantial performance gains with design flexibility over the Rayleigh fading channel.

In this letter, we study the linear processing method to alleviate the intercarrier interference (ICI) for the orthogonal frequency division multiplexing (OFDM) index modulation (IM) in the rapidly time-varying (RTV) channel. Concretely, the proposed linear processing scheme is implemented by the joint design of the transmit precoding and receive postprocessing matrices. First, a lower bound of the capacity of OFDM-IM in the RTV channel is derived. Then, the precoding and postprocessing matrices are designed to maximize this capacity lower bound through utilizing the particle swarm optimization algorithm. Computer simulations show that the proposed scheme can alleviate the ICI effectively and has better performance than the conventional ICI self-cancellation scheme.